5 minutes of reading

Data analysis and Business Intelligence are the main allies in the digital transformation of any company. They are strategic areas explored by those who bet on Information Technology (IT).

This market has an increasing data volume, with new players and new technologies that are updated every minute.

Understanding the direction of the sector and knowing the segment trends are not just ways to gain competitive advantage: they are conditions to survive.

That is exactly why major consultants’ reports are powerful sources of information for you to position yourself in the market.

When it comes to technology research, no one better than Gartner, the global leader in the industry, to provide data and insights, anticipating industry trends.

In this article, we will unravel a report signed by Jim Hare, the company’s vice president, specialized in Business Intelligence and data analysis using huge databases.

The thesis is simple: more and more intelligence will be vital for growth – and survival – of companies that live on technology.

Bearing this thought in mind, Hare listed five industry trends in the Hype Cycle for Analytics and Business Intelligence report, published in 2019. It has to do with data analysis, artificial intelligence and the so-called Business Intelligence, which is about placing intelligence at the heart of the company’s decision making.

The 5 trends of data analysis and Business Intelligence

Before moving on to the five insights gathered by Gartner, it is worth defining data analysis.

Data analysis is the action of preparing, organizing and transforming a set of data to extract from them  relevant information for companies, groups or organizations.

It means analyzing data related to a problem or situation to identify possible solutions.

Was it clear? Check out the main insights gathered by Gartner below:

1. Augmented Analysis growth

Augmented Analysis is a mechanism that facilitates and enhances data analysis, especially when talking about a set of data. It uses machine learning to automate data preparation and data science, including descriptive analysis, predictive analysis and prescriptive analysis.

Gartner predicts that in 2020, the “citizen data scientists,” who take advantage of Augmented Analysis, will outperform data scientists in the amount of data produced.

In an interview with the Datamation portal, Jim Hare  explained that Augmented Analysis means facilitating data handling and communication. “It is making it easier for people to create and deploy these data analysis models, without necessarily having to be a programmer. Therefore, it is really changing the scenario, because it can be done by several professionals,” he projects.

2. Development of a digital culture in companies

For those who aspire to digital transformation, it is essential to pay attention to the development of a digital culture. This lets employees know how to act when dealing with large amounts of data.

The Gartner report explains that the digital culture includes “data literacy, digital ethics, privacy and the use of data for the good of companies and suppliers.”

Establishing a code of ethics is essential to protect your organization and prevent crises related to the inappropriate use of data. Gartner predicts that by 2023, 60% of organizations with more than 20 data scientists will need a professional code of conduct incorporating the ethical use of data analysis.

3. Emergence of Relationship Analysis

How to measure connectivity between institutions, entities, companies, groups of people and individuals in real time? This is what Relationship Analysis proposes.

These are graphic techniques that take into account the location to understand how different entities are connected. It aims to discover how to enhance and stimulate this interaction from the data collected.

Jim Hare explains that Relationship Analysis is based on the comprehension that, in many cases, events cannot be analyzed in isolation. “Today, most of the analytical solutions you see analyze these types of data in isolation,” he says. When analyzing a location, for example, it is possible to look at specific data points on a map. It is also possible to change the analysis to understand how individuals connect and interact in that location.

The result is a richer and more comprehensive analysis, which takes into account the relationship between people and entities.

4. Improvement of decision intelligence

Among the main benefits of data analysis and data science are data-driven decisions: when decision making is driven by data.

For this reason, Gartner predicts that, in the coming years, more and more institutions will seek decision intelligence to optimize results. They will do this with advanced techniques to design, model, align, execute and adjust decision-making models.

In addition, Jim Hare explains that decision intelligence is about seeking a comprehensive approach to problems, taking into account all possible aspects of it. “Decision intelligence is using a combination of AI and automation to break down barriers and really analyze decisions holistically,” he says.

5. More operationalization and scaling

As the data analysis market grows exponentially, it is natural for organizations that need to work with data to look for ways to automate and scale analysis.

Gartner shows that the services and analysis algorithms are a trend for the future, and tend to become popular in different sectors of the market and in companies of all sizes.

In this case, Jim Hare explains that operationalization is about two things: organizations are flooded with data and are trying to figure out how to manage all of that data to get started, but at the same time, they want to understand everything they can do with it.

“The first mission is to discover how to take an increasing amount of data to organize and make it useful for those who need to analyze it. Also, the second is: now that I have analyzed it, who can benefit from these ideas and how to contextualize this information?” Explains the expert.